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Introduction: Traditional methods to derive experimentally-generated relative correction factors (RCFs) for the quantitative analysis of herbal multi-components by single marker (QAMS) method require reference standards and multiple validations with different instruments and columns, which hampers high throughput implementation., Objectives: To effectively reduce the application amounts of raw material and provide higher and more stable accuracy, this study aimed to develop a method to computationally generate RCFs of herbal components., Materials and Methods: This strategy included the published data collection, calibration curves screening, computer algorithm-based RCFs generation and accuracy validation., Results: Using the in silico approach, we have successfully produced 133 RCFs for the multi-component quantitative analysis of 63 widely used herbs., Conclusion: Compared with conventional RCFs, this in silico method would be a low cost and highly efficient way to produce practical RCFs for the QAMS method., (© 2019 John Wiley & Sons, Ltd.)